Agentset

Agentset is a comprehensive RAG-as-a-service (Retrieval-Augmented Generation) platform that enables developers to build sophisticated AI applications without managing complex infrastructure. It's an open-source platform designed for developers and organizations building smart AI tools, including applications for research, company knowledge management, customer support bots, and any system needing to find accurate answers within large document collections.

Agentset processes documents in multiple formats including PDF, TXT, HTML, DOCX, and over 22 file types total. The platform employs advanced retrieval techniques including semantic search, multi-vector embeddings, and intelligent reranking to surface the most relevant results.

The platform includes built-in planning and reasoning features where AI agents can handle multi-step queries, automatically expand queries for comprehensive results, and validate answers to ensure accuracy and reliability. Agentset also supports deep research functionality that takes longer to return results but reviews more sources and provides in-depth answers with greater context.

Agentset automatically cites the sources of answers, allowing users to inspect where information came from.

Agentset reads your documents, breaks them into smaller organized pieces, and converts this information into a format AI can understand. When a question is asked, the platform quickly searches these pieces to find the most relevant parts, then uses this information to generate clear and accurate answers.

The platform offers official JavaScript and Python SDKs with full type safety. You can upload data and get production-ready applications in hours. Agentset also provides a REST API with comprehensive OpenAPI specifications and an MCP server to bring your knowledge base to external applications.

For teams without coding expertise, Agentset supports no-code interfaces where you can configure workflows using simple dropdown menus, with most teams having their first RAG workflow running in under 15 minutes.

Yes, Agentset can process documents in real-time as they're created. Documents can be made searchable within seconds of creation, ensuring your knowledge base stays current.

Agentset is built to handle large document collections and high query volumes. The platform provides self-hosting options for complete control over your infrastructure.

Agentset supports metadata filtering, allowing you to base answers on a subset of your data.

The platform is model-agnostic, letting you select your own vector database, embedding model, and large language model. It integrates with various AI providers including OpenAI, Anthropic, Google AI, xAI Grok, and others.

Built-in observability and performance monitoring help track application performance in production.